#-*-coding:utf-8-*-
import os as path

data_path=path.path.abspath('.')+'/data/'
study_path=data_path+'study/'
compare_path=data_path+'compare/'
study_file=study_path+'historyMessage.txt' #历史基础资料库
sms_word_file=study_path+'smsWords.txt' #历史基础资料 语义化之后的库
sms_category_file=study_path+'smsCategory.txt' #历史基础资料 分类
sms_vocalist_file=study_path+'smsVocalist.npy' #分词之后的词库
sms_spam_file=compare_path+'pWordsSpamicity.txt' #垃圾评论概率模型
spam_file=compare_path+'pSpam.txt' #垃圾评论概率模型
sms_ham_file=compare_path+'pWordsHealthy.txt' #正常评论概率模型
sms_ds_file=compare_path+'trainDS.txt' #DS概率模型
CATEGORY_SPAM = 1 #垃圾评论
CATEGORY_HAMORUNKNOW = 0 #正常或者未知评论
SPLIT_TAB = "\t"
SPLIT_NEXT_ROW = "\n"
SPLIT_SPECIAL = "-"
sms_tmp_file='data/study/tmp_%s'
processCount = 10